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Mapping the Features of an Irrigation Project for Performance Assessment
G. Chandra Mouli
Ph.D Scholar
Department of Agricultural and Food Engineering
Indian Institute of Technology
India
gaddam_chandramouli@yahoo.co.in
S. N. Panda
Professor and Head
School of Water Resources
Indian Institute of Technology
India
snp@agfe.iitkgp.ernet.in
1. Introduction
In general large canal irrigation schemes suffer from in equitable distribution of water due to over-use in head reaches, which is partly caused by farmer preferences for water intensive crop like rice (Bhutta and Velde, 1992). The Irrigation distributary is the basic unit of irrigation management in large canal systems, as it is the last point of control in system operation. Systematic analysis of any irrigation project consisted of identifying problem distributaries and analyzing reasons for the same (Thiruvengadachari and Shakthivadivel, 1997). Spatial and temporal analysis of actual water supply in different parts of the irrigation project can identify how and where to improve the performance of the irrigation scheme (Gaur, 2006). Spatial data management tools like GIS (Geographic Information Systems) can effectively include spatial variability of soil, crop, and water supply in dealing with the complex problems of water resources management (Rao et al, 2004). Chung and Sung (2006) adopted the kriging technique of spatial interpolation of soil properties, with few selected variogram models and maps developed for soil properties in the study clearly showed the presence of both large-scale (trend) variability and small-scale variability, in the small field where it would be reasonable to expect uniformity. Grisso (2007) reported that soil EC maps give valuable information about soil differences and similarities, which makes it possible to divide the field into smaller management zones and indicate areas where further exploration is needed.
2. Study Area
2.1 Location and Extent
The study area is located in the Addanki Branch Canal command of NagarjunaSagar Irrigation project (India). The main source for irrigation is Canal water in addition to some portion of water received from precipitation of South West and North East monsoon seasons. The aerial extent of study area in Irrigation command is about 980 square kilometers situated between latitudes of 15° 41' 24" to 16° 0' 36" North and longitudes of 79° 56' 24" to 80° 17' 56" East. The weather mostly resembles the semi-arid tropical conditions and area experiences prolonged dry spells, which are critical for the survival of crops. The soils in the area are dark grey-brown to black deep clay with fine to very fine texture. The major crops grown are rice and grams besides chillies and cotton as two seasonal crops (Sarma and Rao 1997).
2.2 Specific Problems of Study Area
When the water from the reservoir was first released into canals from Nagarjunasagar reservoir for irrigation in 1967 after its commissioning, only a small portion of the irrigation network was developed. Therefore, in the initial years, farmers were encouraged to cultivate crops of their choice in the areas where irrigation water could reach. As a result, the head-reach and middle-reach farmers took to cultivation of paddy, although these lands do not come under wetland paddy areas as per official localisation scheme. Until 1980, paddy was being cultivated in over 65% of the command area against only 33% earmarked for paddy under the localisation scheme. This gave rise to problems of severe shortage of water particularly in the tail reaches. By the year 1980, when the distribution network in the entire command was nearly complete, water was also needed for the fields at the lower reaches. This necessitated strict adherence to the originally planned localisation scheme for each of the commands of the distributaries in the upper reaches. However, upper-reach farmers continued to grow paddy, and so the lower-reach farmers were deprived of water (Sarma and Rao, 1997).
3. Database
3. 1 Weather
The meteorological data consisting monthly values of precipitation, maximum temperature, minimum temperature, relative humidity, wind speed for 16 years from 1990 to 2005 procured from IMD (Indian meteorological department) for near by weather recording station, Ongole, India have been analysed for assessing the variability.
3. 2 Topographical Maps
In addition to Index map, topographical maps on 1:50000 scale procured from SOI (Survey of India) of numbers 57-M/9, 57-M/10, 57-M/13, 57-M/14, 66-A/1, 66-A/2, 56-A/16, 65-D/4, 66-D/8, 66-A/5 and 66-A/6 have been used in the generation of base map and further extracting features of network of study area.
3. 3 Water Release Data
The daily water release data of 2004-05 from Addanki Branch canal to different off take positions leading in to different distributaries have been procured from the I & CAD (Irrigation & Command area development) department, Government of Andhra Pradesh for analyzing the spatial variability of water release for relating cropping scenario. The fortnightly values of water release are analysed.
3. 4 Ancillary Data
The under ground water levels data for 16 years and covering three representative portions of command area have been procured from the Deputy Director, State ground water department situated at Ongole (AP). Similarly soil, land use data has been procured from Department of Agriculture. Information on crop acreages, change of crop in the region have been taken from Handbook of Prakasam district (Chief planning officer, 2006) as entire study area is located in same district. The yield data of crops is taken from CCE (crop cutting experiments) plots of usually 5 metre x 5 metre size duly identifying their geometric position.
3. 5 Crop Characters
The command area covers simultaneously different distributaries and as well as Mandals (administrative blocks) in Prakasam district of Andhra Pradesh. The salient features of land and crops from different parts of command area procured from various agencies and the Hand book of statistics (Chief planning officer, 2006) of Prakasam District of irrigation project area are presented in table 1. It is positive development to be noted that some farmers are shifting to Irrigated Dry crops in place of Rice (Oryza sativa L.) in view of uncertainty of availability of canal water at lower reaches of command area.
4. Methodology
4. 1 Base Map Generation
Base map preparation was carried out by Chari et al (1994) for a command area, defining the distributary boundaries with the help of topographic maps and district map duly verifying topography and other features. In similar passion using Erdas Imagine soft ware the tophographical maps of the study area are geometrically rectified, taking subset portions of tophosheets mosaic is prepared thus identifying command area. The branch canal and distributaries of irrigation net work are digitized using vector tools of the soft ware and digitized features are compared with the canal net work of geometrically rectified index sketch and district revenue map for integrating command area net work.
4. 2 Spatial Interpolation of Soil Parameters - Theoretical Considerations
The objective of using Kriging technique for spatially interpolating the soil parameters is to predict the salinity parameter values at unmeasured locations, xo, within the system
5. Results and Discussion
5. 1 Spatio- Temporal Distribution of Precipitation.
It is observed that the command area receives rainfall almost equal proportions during both the Southwest and Northeast monsoon seasons. Studying of 16 year record, the upper part of study area received rainfall varying from 907.8 mm in 1996-97 and lowest value of 266.4 in 2004-05, the middle part received more fluctuating quantities of rainfall from 1070 mm in the year 1996-97 to as low as 198.4 in the year 2004-05. Lower part of command area received a maximum value of 1056.7 in 1997-98 and a minimum of 378.2 mm in 2004-05. Dramatically year 2004-05 recorded lowest of rainfall in all three parts of study area as observed in figure 1. In general annual rainfall is observed to be in declining trend for 16 years of reported data. Further the average annual precipitation received in the area is estimated as 849 millimeters and monthly rainfall is observed to increase from June to October and then receded in later part and particularly from December onwards very low amounts have been received. Middle portion has received more variable quantity of precipitation with Cv (coefficient of variance) of 0.4 compared to other two parts estimating Cv at 0.25.
5. 2 Spatial Variability of Water Delivery
The actual canal delivery schedule is observed to be different in different parts as seen in figure 2. It is observed from analysis that 69 %, 25 % and 14 % of design discharges are received at upper, middle and lower parts respectively. The coefficient of variation Cv among three parts is observed to be 0.89, indicating higher variability in water delivery among three parts.
5. 3 Spatial Variability of Ground Water Level
The ground water levels in different portions of command area are shown in figure 3. The upper portion Cv was observed to vary from 0.23 to 0.56 and middle from 0.15 to 0.43 and lower from 0.42 to 0.57 in pre monsoon and post monsoon respectively and similarly MP experienced more ground water level drop compared to other portions. More variability trend in rainfall might have resulted in proportional drop in ground water level. However this effect is being minimized because reliable amount of water received at this section from canal supplies as reported already.
5. 4 The Effect of Salt Concentration.
It is worth to mention that salinity is a measure of the concentration of soluble salts in the soil. Some salts are useful (many fertilizers are in salt form), but too much salt of any kind is detrimental to plants and other organisms. The salt affected soils are characterized by PH and EC (electrical conductivity). The PH readings of soil samples of study area varied from 7.7 to 8.5. Yurtseven et al (2005) stated that crop yield will be decreased with increasing salinity starting from a level of 2.5 dS m-1 besides affecting soil texture.
For some neighboring irrigated locations to the study site it was already reported by Rao et al ( 2003) that moderately salt affected soils are seen in nearly level to very gently sloping portions of land where rice is being cultivated and further valley fringes are found with strong and very strong salinity and sodicity problems.
The analysis indicated that Salinity levels in the most of study area are not posing any threat as they are well below the safe limit. The EC values for other unknown points in the study area were interpolated with ArcGIS software using Geostatistical analyst tool of Arcmap, the results of kriging are shown in figure 4. The predicted EC values to the tune of 0.7 - 0.9, 0.7 - 0.8, and 0.6 - 0.7 have been observed at UP, MP, LP respectively in the prediction map. The analysis was carried out at RMSE of 0.23 of dS m-1 and shown regression function by expression,

Figure 4. Interpolated values of Electrical conductivity of soil in command area
5. 5 Spatial Distribution of Productivity
The productivity of rice crop recorded in upper part is 5879 kg ha-1 (fig. 5) and which is slightly reduced in middle part recording productivity of 98% of upper part but where as lower part recorded productivity of 64% of UP. Similarly canal delivery on an average in UP is 69% of design discharge where as it was as low as 14% in LP. The reasons for considerable fall in productivity at LP could be attributed to very poor canal water delivery. However, on other hand, ID (irrigated dry) crops performed well in LP as observed in terms of productivity. Comparatively higher amount of rainfall and its distribution (table 2) and shallow depth of ground water at LP might be the reasons for favourable growth of dry crops at LP. Productivity of Rice crop has been observed to be higher in both Upper and middle parts as observed in figure 5. The productivity trend noticed here in study area is in agreement with the results observed by Abernethy (1986) that the unequal distribution of water has a direct influence upon production and that part of the system receiving less water than their agronomic requirements will produce less. Crops like Maize and Bengal gram which have established their existence in MP and LP in recent times, registered good performance. Tobacco crop also performed well in the lower portion of command area.
6. Conclusions
Rice crop recorded good performance in distributaries located in upper part compared to the lower part because of solely good amounts of canal delivery. Shortfall of delivery of canal water affected productivity at LP. As stiff competition exists among farmers of various parts for share of water for the staple crop rice, attention is required for equitable distribution of water in different locations of command area. Because of geospatial analysis of EC, estimates for any point could be predicted besides visualizing salinity scenario in entire canal command. It is also noticed that EC level decreased from upper to lower portion even though it is under safe limits in entire study area.
7. Acknowledgements
The authors express their gratitude to the Assistant Director of Agriculture, Prakasam District, Department of Agriculture, Government of Andhra Pradesh for extending laboratory facilities for testing core samples of soil at Ongole, Andhra Pradesh, India. The authors also thank office of Irrigation & CAD, Addanki, Prakasam district, Andhra Pradesh for providing water release and ancillary data and assisting during field visits.
8. References
Abernethy, C.L. 1986. Performance measurements in canal water management. a Discussion, ODI-IIMI Irrigation Management Network Paper, 86/2d.
Bhutta, M.N., Van der Velde, E.J. 1992. Equity of water distribution along secondary canals in Punjab, Pakistan. Irrigation Drainage Systems 6(2):161-177
Thiruvengadachari, S., Jonna, S., Raju, P.V., Murthy, C.S. and Hakeem, K.A. 1994. System performance evaluation and diagnostic analysis of canal irrigation projects. Paper presented at the 15th Asian conference on remote sensing. Survey Department, Sri Lanka and Asian Association on Remote Sensing (AARS), New Delhi, 17-23 November 1994
Chief planning officer. 2006. Agriculture. In: Hand book of Statistics 2004-05. Prakasam district, Ongole, Andhra Pradesh, India
Chung, S. and Sung, J. 2006. Spatial variability of yield, chlorophyll content, and soil properties in a Korean rice field. Precision farming machinery laboratory, bio-production division, National Agricultural Mechanization Research Institute, RDA Suwon, Republic of Korea
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